Sr. Data Engineer

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.5+ yrs. experience in data engineering roles.3+ years of experience in DWH/ETL Domain using AWS tech stack such as Redshift, S3, Glue, Lambda and IAM.Proficiency in PySpark/Python/SQL and designing data models and data standards.Deep understanding of ETL/ELT processes, data warehousing concepts, and big data technologies.Experience building & managing data pipelines using tools like Glue, Airflow, AWS Step Functions, or similar.Experience in RDMS & No-SQL databases: SQL Server databases, PostgreSQL, DynamoDB, or Aurora.Experience in dimensional modeling & schema design; Star and Snowflake modelProven ability to lead & mentor data engineers towards innovative and disciplined environment.Strong problem-solving skills, with a process/methodical approach to resolve technical challenges and risksExcellent analytical, verbal and communication skills for stakeholder and team management. Initiate/Incubate/execute PoCs to validate the use cases targeting enhanced ETL/DWH engineering solutions.Provide Architectural Guidance the team about data pipelines/ storage/ operations/ client delivery.Initiate and drive cost optimization programs leverage design & Infra enhancements.Implement best practices for data engineering, ETL, and DWH development in AWS cloud environmentConduct code reviews; Coach team members on coding practices and drive adherence to coding standards.Collaborate with cross-functional teams to finalize project requirements, timelines, and deliverables.Monitor project progress, identify risks, and ensure on-time delivery of data engineering projects.Optimize data models for performance and scalability; leverage latest AWS services to supplement scalable and configurable DWH architectures